Images, or portions thereof, may be blurry for a variety of reasons. An image may be blurry due to motion blur, for example. Motion blur may be present when an object captured in an image moves relative to a camera capturing the image over a period of exposure, e.g., a period of time during which the camera's shutter is open and film or an imaging sensor is exposed to incoming light.
An image may also be blurry due to defocus blur. Defocus blur may be present in an image, for instance, due to a camera's depth of field (DOF), which refers to a distance between the nearest and farthest objects in a scene that appear sharp in an image captured by the camera. Objects within a camera's DOF appear sharp in an image, while objects in front of and beyond the camera's DOF appear blurry.
Regardless of a cause of blur, its estimation may have a variety of applications. Estimation of defocus blur may be useful, for instance, to detect and segment an in-focus subject from an out-of-focus background of an image. To convey the results of estimating defocus blur, a defocus blur map may be generated. However, conventional techniques for estimating defocus blur and for generating a defocus blur map can consume significant computing resources. Consequently, defocus blur estimation may not be suitable for some applications.